Business are often faced with the task of associating consumer-specific attributes that have importance with respect to marketing campaigns to individuals whose relevant data as known to the business contains incomplete and/or indirect contact information. Without the ability to associate this consumer data to specific, well-defined individuals, the value of this data is significantly diminished. Important examples in online marketing environments include situations where the only available information is a “handle” for the individual, such as an email address or an identifier used in various social media channels, such as Twitter handles and Facebook user names.
Handles may be parsed in order to look for identifying information. Existing parsing applications often give exclusive focus on the identification of first, middle, and last names embedded in an input string, and use fuzzy string matching to find variations of traditional names. Although such approaches may work well for strings primarily composed of names, most of these handles contain either limited traditional name components and/or phrases that identify traits and characteristics of the individual. Very small changes in a given name can result in a word/phrase that clearly describes a personal attribute, and hence the use of fuzzy string matching in these cases may yield poor results.
Marketing efforts vary between the identification of a specific individual for direct marketing and the association of groups of individuals that share interests for online marketing. The association of these handles with a particular individual, or their association with traits associated with certain types of individuals, would be of great value in marketing campaigns, such as the formulation of marketing messages targeted to such individuals.